Metadata-based emitter localization

ABSTRACT

A method includes obtaining signal information corresponding to a plurality of radio signals received at two or more sensing devices from a candidate location, determining a plurality of reconstructed signals based on the signal information, determining time-estimates and frequency-estimates based on a correlation between the plurality of radio signals and the plurality of reconstructed signals, determining metadata corresponding to the plurality of radio signals based on the signal information, the time-estimates, or the frequency-estimates, transmitting at least a portion of the metadata to an information combining node, obtaining the portion of the metadata from the information combining node, determining a relationship between the metadata, and determining the candidate location based on the metadata and the relationship between the metadata. Transmission of the plurality of radio signals to the information combining node is restricted based on a bandwidth of the two or more sensing devices or the information combining node.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of priority under 35 U.S.C. § 119(e)of U.S. Provisional Application No. 62/575,097, filed on Oct. 20, 2017,and entitled “Distributed System for Metadata Based Many-EmitterLocalization,” which is incorporated herein by reference in itsentirety.

TECHNICAL FIELD

The following disclosure relates generally to systems and techniques fordetermining emitter locations based on metadata corresponding to radiosignals.

BACKGROUND

Various electrical devices emit radio signals. For example,communications radios, emergency safety beacons, radars, televisionbroadcast towers, wireless access points, cellular towers, cellularphones, and satellite phones, among other radio emitters, transmit radiosignals that can be received by other devices.

SUMMARY

The present disclosure describes devices, systems and techniques fordetermining locations of electrical devices based on receiving, by twoor more sensing devices, radio signals emitted by the electricaldevices. The radio signals received by the two or more sensing devicesare processed to determine metadata descriptive of the received radiosignals. A receiver station receives the metadata from the two or moresensing devices, and determines locations of the electrical devicesbased on the metadata and a relationship between the metadata receivedfrom the different sensing devices. In this context, a receiver stationthat receives metadata from a sensing device is referred to as aninformation combining node, while an electrical device that emits aradio signal is referred to as an emitter or a wireless transmitter, anda sensing device that receives radio signals from an emitter is referredto as a sensor.

In some implementations, the sensors are located on board two or moremobile platforms. The mobile platforms receive radio signals fromemitters, process the radio signals to determine metadata that isdescriptive of the received radio signals, and sending the metadata toan information combining node to determine locations of the emitters.The metadata may include, for example, descriptive informationcorresponding to time-estimates and frequency-estimates of the radiosignals arriving at the mobile platforms. In some implementations, themobile platforms are orbiting satellites. In some implementations, thecorresponding information combining node is a satellite ground station.

In some implementations, one or more sensors may perform actions toobtain optimal matching for the radio signal of interest that may havearrived at the one or more sensors with frequency offsets, differentpulse shapes, filter parameters, or other variations that may lead toerrors or reductions in accuracy for spatial localization ifunaddressed. The one or more sensors may limit outgoing communicationsto the information combining nodes to include only metadata thatdescribes detected emissions rather than full or partial recordings ofthe radio signals, which may decrease a volume of communications andstorage cost at the one or more sensors. In this context, spatiallocalization refers to operations to locate radio emitters with acertain level of confidence based on analysis of radio signals emittedby the radio emitters. For example, a location or high likelihood regionof the radio emitter may be determined based on a frequency or time ofthe radio signals emitted from the radio emitter. In some cases, asystem for spatial localization includes one or more sensors configuredto receive radio signals emitted from radio emitters.

According to one aspect of the subject matter described in thisapplication, a method includes: obtaining, from a first sensing device,first information corresponding to a first radio signal received at thefirst sensing device from a candidate location; determining a firstreconstructed signal corresponding to the first radio signal based onthe first information; determining at least one of a first time-estimateor a first frequency-estimate based on a correlation between the firstradio signal and the first reconstructed signal; and determining firstmetadata corresponding to the first radio signal based on at least oneof the first information, the first time-estimate, or the firstfrequency-estimate. The method further includes: obtaining, from asecond sensing device, second information corresponding to a secondradio signal received at the second sensing device from the candidatelocation; determining a second reconstructed signal corresponding to thesecond radio signal based on the second information; determining atleast one of a second time-estimate or a second frequency-estimate basedon correlation between the second radio signal and the secondreconstructed signal; determining second metadata corresponding to thesecond radio signal based on at least one of the second information, thesecond time-estimate, or the second frequency-estimate.

The method further includes: transmitting at least one of the firstmetadata or the second metadata to an information combining node;obtaining, from the information combining node, at least one of thefirst metadata or the second metadata; and determining a relationshipbetween the first metadata and the second metadata, and determining thecandidate location based on the first metadata, the second metadata, andthe relationship between the first metadata and the second metadata. Forexample, the method uses one or more or a timing difference of arrival,a frequency difference of arrival, or other relationship included in themetadata to determine likely candidate locations of emitters of radiosignals. Transmitting at least one of the first metadata or the secondmetadata to the information combining node includes restrictingtransmission of the first radio signal and the second radio signal tothe information combining node based on a bandwidth of the first sensingdevice, the second sensing device, or the information combining node.

Implementations according to this aspect may include one or more of thefollowing features. For example, determining the candidate location mayinclude determining the candidate location based on at least one of thefirst metadata received at the information combining node or the secondmetadata received at the information combining node. A bandwidth fortransmitting the first metadata from the first sensing device may beless than a bandwidth for transmitting the first radio signal from thefirst sensing device, and a bandwidth for transmitting the secondmetadata from the second sensing device may be less than a bandwidth fortransmitting the second radio signal from the second sensing device. Inthe same or other examples, a memory space for storing the firstmetadata from the first sensing device is less than a memory space forstoring the first radio signal from the first sensing device, and amemory space for storing the second metadata from the second sensingdevice is less than a memory space for storing the second radio signalfrom the second sensing device.

In some implementations, transmitting at least one of the first metadataor the second metadata to the information combining node may includetransmitting the first metadata and the second metadata through acommunications bus communicably coupled to the information combiningnode. For example, the communications bus may have a band of frequenciesthat includes at least one of a VHF-band, a UHF-band, an S-band, aKu-band, a Ka-band, or an X-band that are configured to carry a radiosignal.

In some implementations, obtaining the first information includesgenerating a data stream by digitizing the first radio signal, andobtaining, from the data stream, information derived from the firstradio signal. For example, obtaining the information derived from theradio first signal may include obtaining, from the data stream, at leastone of a time of arrival of the first radio signal at the first sensingdevice, a frequency of the first radio signal at the time of arrival, afrequency offset associated with the first radio signal, a signal tonoise ratio associated with the first radio signal, information bitsincluded in the data stream corresponding to the first radio signal, ora signal parameter that defines one or more features of the first radiosignal, such as spectral shape, or frequency roll-off, among others.

In some examples, determining the first reconstructed signal may includedetermining the first reconstructed signal based on at least one of thetime of arrival of the first radio signal at the first sensing device,the frequency of the first radio signal at the time of arrival, thesignal to noise ratio of the first radio signal, the signal parameterthat defines one or more features of the first radio signal, theinformation bits included in the first radio signal, or the signalparameter that defines the shape of the first radio signal. In someexamples, determining the first metadata corresponding to the firstradio signal may include determining descriptive informationcorresponding to at least one of the time of arrival of the first radiosignal at the first sensing device, the frequency of the first radiosignal at the time of arrival, the signal to noise ratio of the firstradio signal, the information bits included in the first radio signal,or the signal parameter that defines one or more features of the firstradio signal.

In some implementations, obtaining the second information may includegenerating a data stream by digitizing the second radio signal, andobtaining, from the data stream, information derived from the secondradio signal. For example, obtaining the information derived from thesecond radio signal may include obtaining, from the data stream, atleast one of a time of arrival of the second radio signal at the secondsensing device, a frequency of the second radio signal at the time ofarrival, a frequency offset associated with the second radio signal, asignal to noise ratio associated with the second radio signal,information bits included in the data stream corresponding to the secondradio signal, or a signal parameter that defines one or more features ofthe second radio signal.

In some examples, determining the second reconstructed signal mayinclude determining the second reconstructed signal based on at leastone of the time of arrival of the second radio signal at the secondsensing device, the frequency of the second radio signal at the time ofarrival, the signal to noise ratio of the second radio signal, thesignal parameter that defines one or more features of the second radiosignal, the information bits included in the second radio signal, or thesignal parameter that defines one or more features of the second radiosignal. In some examples, determining the second metadata correspondingto the second radio signal may include determining descriptiveinformation corresponding to at least one of the time of arrival of thesecond radio signal at the second sensing device, the frequency of thesecond radio signal at the time of arrival, the signal to noise ratio ofthe second radio signal, or the information bits included in the datastream corresponding to the second radio signal.

In some implementations, determining the first metadata corresponding tothe first radio signal may include determining descriptive informationcorresponding to at least one of a first time of arrival at which thefirst radio signal arrived at the first sensing device, or a firstfrequency of arrival of the first radio signal received at the firstsensing device at the first time of arrival. In such implementations,determining the second metadata corresponding to the second radio signalmay include determining descriptive information corresponding to atleast one of a second time of arrival at which the second radio signalarrived at the second sensing device, or a second frequency of arrivalof the second radio signal received at the second sensing device at thesecond time of arrival.

In some implementations, determining the candidate location may includeobtaining information regarding a trajectory of at least one of thefirst sensing device or the second sensing device, and identifying acandidate emitter corresponding to the first radio signal and the secondradio signal based on at least one of the information regarding thetrajectory of at least one of the first sensing device or the secondsensing device, the relationship between the first metadata and thesecond metadata, the first metadata, or the second metadata. Forexample, identifying the candidate emitter may include obtaininginformation regarding the candidate emitter, determining whether thefirst metadata or the second metadata corresponds to the informationregarding the candidate emitter, and identifying the candidate emitterbased on a determination that the first metadata or the second metadatacorresponds to the information regarding the candidate emitter.

In some examples, determining the candidate location may further includedetermining the candidate location from estimated locationscorresponding to the information regarding the candidate emitter, thetrajectory of at least one of the first sensing device or the secondsensing device, the relationship between the first metadata and thesecond metadata, the first metadata, and the second metadata. Forexample, the information regarding the candidate emitter may include atleast one of a type of the candidate emitter, a history of locations ofthe candidate emitter, a travel schedule of the candidate emitter, afrequency band of an emission from the candidate emitter, a frequencyoffset of the emission, a pulse shape, a modulation parameter, or othersignal parameters of the emission, or acoustic content (e.g., voice,music, or other sounds) included in the emission.

In some implementations, obtaining the information regarding thecandidate emitter may include obtaining the information regarding thecandidate emitter from at least one of the first metadata, the secondmetadata, the first sensing device, the second sensing device, anothersensing device, an information repository, or an internet source thatspecifies a type of the candidate emitter, a travel schedule of thecandidate emitter, information indicating an emitter mode, or afrequency band of an emission from the candidate emitter.

In some implementations, the method may further include storinginformation corresponding to the candidate emitter and the candidatelocation in a non-transitory storage medium. In some implementations,the method may further include transmitting information corresponding tothe candidate emitter and the candidate location to a communications busor to an information processing node.

In some implementations, one or both of the first sensing device and thesecond sensing device may include at least one of a Low Earth Orbit(LEO) satellite, a Medium Earth Orbit (MEO) satellite, a GeosynchronousOrbit (GEO) satellite, a Highly Elliptical Orbit (HEO) satellite, a nanosatellite, an unmanned aerial vehicle (UAV), a terrestrial vehicle, aspacecraft, a stationary terrestrial sensor, or a mobile platform. Insome cases, the first sensing device includes the second sensing device,and the first sensing device is configured to receive a plurality ofradio signals. In such cases, obtaining the second informationcorresponding to the second radio signal includes obtaining the secondinformation corresponding to the second radio signal that is received atthe first sensing device.

In some implementations, the first sensing device or the second sensingdevice includes the information combining node in which transmitting atleast one of the first metadata or the second metadata to theinformation combining node may include transmitting at least one of thefirst metadata or the second metadata to one of the first sensing deviceand the second sensing device that includes the information combiningnode.

In some implementations, determining the first and second reconstructedsignals may include minimizing a distance metric respectivelycorresponding to a difference between the first reconstructed signal andthe first radio signal and between the second reconstructed signal andthe second radio signal. For example, the distance metric may include amean squared value corresponding to the difference between the firstreconstructed signal and the first radio signal or the differencebetween the second reconstructed signal and the second radio signal.Alternatively or in addition, determining the first and secondreconstructed signals may include minimizing a cost metric or a costfunction, other than the distance metric described above, respectivelycorresponding to a difference between the first reconstructed signal andthe first radio signal and between the second reconstructed signal andthe second radio signal.

In some implementations, the information combining node may include aplurality of information combining nodes such as a data center, a shipcontrol center, or a satellite control center.

Implementations of the above techniques include methods, apparatus,computer program products, and systems for performing theabove-described actions. Such a computer program product may be embeddedin a non-transitory machine-readable medium that stores instructionsexecutable by one or more processors. The instructions are configured tocause the one or more processors to perform the above-described actions.Such a system includes two or more sensing devices, one or moreprocessors, and a storage medium storing instructions that, whenexecuted by the one or more processors, are configured to cause the oneor more processors to perform the above-described actions upon receivingradio signals from the sensing devices.

The systems and techniques described herein enable spatial localizationof emitters without relying on an algorithm that assumes ability forcommunicating radio signals or resources for processing the radiosignals and additional information (e.g., integration and comparison ofthe additional information). For instance, a conventional method mayinclude a filter, which may not match well the radio signals, or a datacommunication link outside of a limited bandwidth for transmission of acorrelation output of the radio signals or a compressed version of anambiguity function corresponding to the radio signals. In this regard,the conventional method may overlook a critical signal processingresource needed for an optimal performance of its subsystems for spatiallocalization. By contrast, the systems and techniques described hereincan provide accurate spatial localization of emitters using sensingdevices with limited hardware resources, e.g., bandwidths forcommunicating the metadata between the sensing devices or between theinformation combining node and the sensing devices, or limited storagespace for holding signal information. In addition, hardware resources(e.g., a capacity of memory, a computing power or speed) for processingthe metadata are less than hardware resources for processing the radiosignals in conventional approaches.

Accordingly, the techniques described herein are useful to scale thedisclosed systems to a distributed system including many sensorsconfigured to receive radio signals from many emitters. For instance,the disclosed techniques based on metadata is useful for spacecraft,e.g., satellites, which have limited processing resources andconstrained communication bandwidths. As another example, in aconstellation including a plurality of satellites, the techniquesdescribed herein are useful to perform localization of one or moreemitters based on low bandwidth information sharing techniques betweenthe sensors of the satellites.

The details of one or more disclosed implementations are set forth inthe accompanying drawings and the description below. Other features,aspects, and advantages will become apparent from the description, thedrawings and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example of a system for determining emitterlocations, according to one or more implementations.

FIG. 2A illustrates a block diagram of an example of a single sensingdevice in a distributed localization system, according to one or moreimplementations.

FIG. 2B illustrates a block diagram of an example of multiple sensingdevices in a distributed localization system, according to one or moreimplementations.

FIG. 3 illustrates a block diagram of an example of an informationcombining node in a distributed localization system, according to one ormore implementations.

FIG. 4 illustrates an example of a distributed system for determiningemitter locations, according to one or more implementations.

FIG. 5 illustrates an example of a process for determining emitterlocations based on metadata corresponding to radio signals, according toone or more implementations.

FIG. 6 illustrates an example of a process for identifying a candidatelocation at an information combining node, according to one or moreimplementations.

DETAILED DESCRIPTION

Disclosed are systems and techniques that enable a distributed systemfor spatial localization of radio emitters based on metadatacorresponding to emissions from the radio emitters that are received bya plurality of distributed radio sensor platforms (e.g., smallsatellites). In some cases, the radio sensor platforms, also referred toas mobile platforms, may be restricted from transferring or storing theraw emissions (e.g., radio signals) due to limited resources. However,the limited resources (e.g., bandwidth, storage space) of the radiosensor platforms may be sufficient to transmit or receive the metadatacorresponding to the raw emissions and to store the metadata orlocalization results (e.g., history of locations of the emitters) basedon analysis of the metadata. For instance, the metadata corresponding toradio signals provide descriptive information about the radio signals(e.g., a time instant of arrival, a frequency, a signal parameter, anoise level, content or header bits, etc.), which may significantlyreduce resources needed for operations of the radio sensor platformssuch as spatial localization operations to locate the radio emitters ormore generally store or transmit descriptions of emissions compactly.

In some implementations, the distributed system includes hardwaresubsystems (e.g., two or more radio sensor platforms, one or morereceiver stations) and a corresponding logic that can run on acollection of distributed radio sensor platforms (e.g., on smallsatellites). Additionally or alternatively, one or more informationcombining nodes may perform spatial localization of radio emitterswithout transferring or storing a large amount of information.Transferring or storing a large amount of information may be impracticalfor a distributed sensor system such as a system of small satellites. Adistributed system design is critical to the ability for scaling thenumber of emitters to be localized, and the number of sensorseffectively used for localization, while meeting practical hardware andsystem constraints.

FIG. 1 illustrates an example of a system 100 for determining emitterlocations, according to one or more implementations. The system 100includes sensing devices 102, 104 and 106, an area 110 that includes aplurality of emitters that are indicated by candidate emitter locations112, 114, 116, 118, and 119, and an information combining node 140.

In some implementations, the sensing devices 102, 104 and 106 are mobileapparatus, such as spacecraft, aerial vehicles, terrestrial vehicles, orsome or suitable mobile platforms. For example, the sensing devices 102,104, and 106 are satellites. Alternatively, the sensing devices 102,104, and 106 are cars, trucks, or ships. Alternatively, the sensingdevices 102, 104, and 106 are aerial vehicles such as airplanes, orunmanned aerial vehicles (UAVs) such as drones or balloons. In someimplementations, the sensing device 102 is a first type of mobileplatform, while the sensing devices 104 and 106 are a second type ofmobile platform that is different from the first type of mobileplatform. For example, the sensing device 102 can be a satellite, whilethe sensing devices 104 and 106 can be terrestrial vehicles, or viceversa. Alternatively, the sensing device 102 can be a satellite, thesensing device 104 can be a terrestrial vehicle, and the sensing device106 can be an UAV.

Each sensing device includes one or more radio signal receivers, alsoreferred to as sensors, which are configured to receive radio signalsfrom emitters. In some implementations, the sensors correspond to radiofrequency (RF) antennas coupled to transponders and/or networkinterfaces on board the sensing devices. Each sensing device can alsoinclude other hardware components, such as a digitizer (e.g., an analogto digital converter, or ADC) that converts the received analog radiosignals to digital format, one or more processors, and memory thatstores instructions corresponding to operations performed by the sensingdevice, and also stores the radio signal data and/or processedinformation generated based on the radio signal data.

Although three sensing devices 102, 104, and 106 are shown, in someimplementations the system 100 includes a different number of sensingdevices. For example, the system 100 can include two sensing devices(e.g., 102 and 104) or four or more sensing devices.

In some implementations, the area 110 is a geographic region on theEarth's surface or oceans. In some implementations, the area 110 is aregion of space that is proximate to the Earth's surface or oceans,e.g., at a height of a few feet to a few tens or hundreds of feet aboveground. The emitters corresponding to the candidate locations 112, 114,116, 118, and 119 include one or more of emergency safety beacons,radars, marine radars, automatic identification system (AIS)transceivers, television broadcast towers, wireless access points,wireless transmitters, cellular towers, cellular phones, and satellitephones, among other radio emitters. In some implementations, differentemitters corresponding to the candidate locations 112, 114, 116, 118,and 119 are of different types. In other implementations, the emitterscorresponding to the candidate locations 112, 114, 116, 118, and 119 areof the same type. Each emitter includes hardware, such as one or morecommunications radios or other types of radio transmitters (e.g.,radar), which transmit radio signals that can be received by otherdevices, such as the sensing devices 102, 104, and/or 106.

The sensing devices 102, 104, and 106 are mobile, with sensing device102 moving with a trajectory 102 a, sensing device 104 moving with atrajectory 104 a, and sensing device 106 moving with a trajectory 106 a.Depending on the type of the sensing device, the movement of the sensingdevices 102, 104 and 106 are in space in some implementations, or on theterrestrial surface in some other implementations. In implementationswhere one or more of the sensing devices are aerial platforms, thesensing devices follow trajectories through space. For example, thesensing devices can include satellites that follow orbital trajectorieswith respect to the Earth's surface. Alternatively, in implementationswhere one or more of the sensing devices are terrestrial vehicles, thesensing devices follow trajectories on the ground. For example, thesensing devices can include cars or trucks that travel on the Earth'ssurface, either along marked roads or on unmarked areas. As anotherexample, the sensing devices can include boats or ships that travel onwater, such as the oceans.

During movement of the sensing devices 102, 104, and 106 along theirrespective trajectories, the sensing devices 102, 104, and 106 receiveradio signals from one or more emitters located at one or more of thecandidate locations 112, 114, 116, 118, and 119. For example, during aknown time interval, the sensing device 102 receives radio signal 112 afrom an emitter at candidate location 112 when the sensing device 102 isat a first location in its trajectory 102 a, and subsequently receivesradio signal 112 b from the emitter at the candidate location 112 whenthe sensing device 102 is at a second location in its trajectory 102 aduring the time interval. The sensing device 104 receives radio signal112 c from the emitter at the candidate location 112 when the sensingdevice 104 is at a first location in its trajectory 104 a, andsubsequently receives radio signal 112 d from the emitter at thecandidate location 112 when the sensing device 104 is at a secondlocation in its trajectory 104 a. In some implementations, one of theradio signals 112 a or 112 b is same as one of the radio signals 112 cor 112 d.

For example, a signal emitted by the emitter at the candidate location112 at a time instant and received by the sensing device 102 can bereferred to as the radio signal 112 a, while the same signal received bythe sensing device 104 can be referred to as the radio signal 112 c.Additionally or alternatively, a signal emitted by the emitter at thecandidate location 112 at a second time instant and received by thesensing device 102 can be referred to as the radio signal 112 b, whilethe same signal received by the sensing device 104 can be referred to asthe radio signal 112 d. One or more of the sensing devices 102, 104 and106 can similarly receive radio signals from other emitters while movingalong their respective trajectories.

In some implementations, time delay and Doppler frequency offsettrajectories are computed for the sensing devices based on the receivedsignals along the paths to specific candidate spots in the area 110. Inthis context, time delay is due to the propagation of electromagneticwaves through free space as they travel between an emitter and areceiving sensor. In some instances, different characteristics of thepropagation (e.g., timing, distortion, or frequency of signal arrival)is affected by additional mediums or effects, such as effects due topropagation through the ionosphere, dispersion, or due to other sourcesthat can be modeled and accounted for distinct from a free space model.The Doppler frequency offset refers to the translation of the centerfrequency of a signal due to relative velocity differences between thesignal emitter and the sensor receiving the signal. By computing thetime delay and Doppler frequency offset trajectories from the knownpaths of the sensing devices, signals arriving from a particularlocation can be coherently added. For example, time delay and Dopplerfrequency offset trajectories are computed for the sensing devices 102and 104 based on their known trajectories 102 a and 104 a, respectively.Following computation of the time delay and Doppler frequency offsettrajectories for the sensing devices 102 and 104, the signals from theemitter at the candidate location 112 that are received at the sensingdevice 102 (e.g., on one or more of the radio signals 112 a and 112 b),and the signals from the emitter at the candidate location 112 that arereceived at the sensing device 104 (e.g., one or more of the radiosignals 112 c and 112 d) are coherently added.

As noted above, in some implementations, one or more of the sensingdevices 102, 104, and 106 are satellites. In such cases, the satellitesinclude one or more of a Low Earth Orbit (LEO) satellite, a Medium EarthOrbit (MEO) satellite, a Geosynchronous Orbit (GEO) satellite, a HighlyElliptical Orbit (HEO) satellite, a nano satellite, or an unmannedaerial vehicle (UAV). In some implementations, some of the sensingdevices are satellites while the others are different types of mobileplatforms, e.g., aerial or terrestrial vehicles. The different types ofsensing devices in a multi-platform implementation can contribute togreater diversity or increased differentiation of values of delay andDoppler offset between the sensing devices. In some implementations,radio signals may be received at the plurality of sensing devices (e.g.,sensing devices 102, 104, and 106) from a plurality of candidate emitterlocations (e.g., from emitters corresponding to the candidate locations112, 114, 116, 118, and 119).

In some implementations, the information combining node 140 receivesmetadata corresponding to radio signals received at sensing devices, andperforms spatial localization of emitters that has emitted the radiosignals. For example, a communications link 134 is established betweenthe sensing device 102 and the information combining node 140, while acommunications link 136 is established between the sensing device 104and the information combining node 140. In some examples, the metadatacorresponding to the radio signals determined at the sensing devices maybe transmitted to one or more receiver station such as an informationcombining node 140. Each of the communications link 134 and thecommunications link 136 has a sufficient bandwidth for transferring themetadata corresponding to the radio signals received at the respectivesensing devices, while the bandwidth may be limited for transferring theradio signals, a compressed radio signals, or a portion of the radiosignals. In some instances, these communications links are intermittent,for instance, when not in touch with a ground station, in which messagesmay be queued or stored for later transmission (e.g., upon linkestablishment). In other instances, the communications links are alwaysmaintained to enable communication between the sensing device and theground station.

For example, the sensing device 102 sends to the information combiningnode 140, over the communications link 134, first metadata that aredetermined at the sensing device 102 based on a first radio signal suchas the radio signals 112 a and 112 b emitted from the emitter at thecandidate location 112. Similarly, the sensing device 104 sends to theinformation combining node 140, over the communications link 136, secondmetadata that are determined at the sensing device 104 based on a secondradio signal such as the radio signals 112 c and 112 d received from theemitter at the candidate location 112.

In some implementations, the information combining node 140 may controland/or monitor the operations performed by the sensing devices. Forexample, the information combining node 140 sends instructions to thesensing devices 102, 104 and/or 106, to control the movement of thesensing devices along their respective trajectories, to operate theirsensors to receive signals from ground emitters, and/or to send themetadata to the information combining node 140 at preselected timeintervals or upon determination of the metadata. The instructions sentfrom the information combining node 140 control at what locations alongthe respective trajectories (e.g., along trajectory 102 a for sensingdevice 102 or along trajectory 104 a for sensing device 104) the sensingdevices operate their corresponding sensors to receive the signals. Insome cases, the information combining node 140 may also utilizes thetrajectory information as well as the metadata to perform spatiallocalization.

The information combining node 140 may include a gateway with RFtransponders or an optical communication link, which receives themetadata from the sensing devices 102, 104, and 106 in someimplementations. For example, when one or more of the sensing devicesare spacecraft, the information combining node 140 can include aterrestrial satellite gateway that communicates with the spacecraft. Insome implementations, one or more of the sensing devices 102, 104, and106, among others, forward to the gateway the metadata corresponding toradio signals that are received at the sensing devices from theemitters.

In some implementations, the sensing device 104 sends, over acommunications link 132 established between the sensing devices 102 and104, the metadata that are determined at the sensing device 104 based onradio signals such as the radio signals 112 c and 112 d received fromthe emitter at the candidate location 112. In such implementations, asensing device (e.g., sensing device 102) may perform operations forspatial localization of the emitter (e.g., the emitter at the candidatelocation 112) based on the metadata determined at the sensing device 102and the metadata received from a different sensing device (e.g., sensingdevice 104).

In some implementations, a sensing device may control and/or monitor theoperations performed by the other sensing devices. For example, thesensing device 102 sends instructions to the sensing devices 104 and/or106, to control the movement of the sensing devices along theirrespective trajectories, to operate their sensors to receive signalsfrom ground emitters, and/or to send the metadata to the informationcombining node 140 or the sensing device 102 at preselected timeintervals or upon determination of the metadata. The instructions sentfrom the sensing device 102 control at what locations along therespective trajectories (e.g., along trajectory 104 a for sensing device104) the sensing devices operate their corresponding sensors to receivethe signals.

The information combining node 140 performs the various computationsbased on receiving the metadata from the sensing devices. In someimplementations, operations for spatial localization of emitters basedon the metadata are performed at the information combining node 140within a datacenter environment. The techniques for spatial localizationcan be executed at the site of the information combining node 140, orforwarded (e.g., through a dedicated physical communications link orover an Internet connection) to a datacenter that is connected to theinformation combining node 140.

FIG. 2A illustrates a block diagram of an example of a distributedlocalization system 200 a, according to one or more implementations. Thesystem 200 a includes a sensing device 202 that receives radio signalsemitted from a radio emitter 212 through a communication path, e.g., aradio channel 220, and an information combining node 240 that receivesmetadata corresponding to the radio signal from the sensing device 202through a communications bus 230. In some examples, the system 200 a mayinclude one or more sensing devices 202, and one or more informationcombining nodes 240. The system 200 a may correspond to the system 100in FIG. 1, and the sensing device 202 may corresponds to any one of thesensing devices 102, 104, or 106 in FIG. 1.

In some implementations, the sensing device 202 includes an antenna 252that receives radio signals, a digitizer 254 (e.g., an ADC) that covertsthe received radio signals to a data stream of discrete digital signals,a signal detector 256 that monitors the data stream to detect anoccurrence of an emission from the emitter 212, and a signal demodulator258 that determines information derived from the radio signals based onthe data stream. In some implementations, the sensing device 202 furtherincludes a remodulator 262 that generates reconstructed signals based onthe information derived from the radio signals, a matched filter 264that generates a correlation between the radio signals and thereconstructed signals, and a time & frequency estimator 266 thatdetermines a time of arrival (TOA) and a frequency of arrival (FOA) ofthe radio signals. The sensing device 202 determines a metadata 109 thatincludes one or more of TOA and FOA results.

In some examples, as described above, a radio emitter 212 (e.g.,cellular radio towers, broadcast radio towers, ships with beacons,vehicles with voice or data communications radios, etc.) emits radiosignals through one or more radio channels 220 in radio frequencies. Thesensing device 202 receives the radio signals that may have beenattenuated, distorted, or delayed through propagation through the radiochannel 220 prior to reception by the sensing device 202 (e.g., a smallsatellite). For example, the sensing device 202 receives wirelessemissions such as the radio signals using the antenna 252 that detectsradio frequency. The sensing device 202 further includes a receiver ortuner and a digitizer 254, which process (e.g., tune and digitize) theradio signals detected by the antenna 252. For example, the digitizer254 converts the received analog radio signal to digital signals togenerate a data stream of digital signals.

The sensing device 202 includes a signal detector 256 that monitors thedata stream generated by the digitizer 254 to detect an occurrence of anemission that matches predetermined properties of a target signal type.For example, the signal detector 256 may include a matched filter, acyclostationary detector, an energy detector, or other detection methodsand algorithms that look for an occurrence of an emission in the datastream of the digitized radio signals and that look for matching betweenthe emission and certain properties of a target signal type (e.g.,cyclostationary properties, energy, preamble values, etc.).

The sensing device 202 includes a signal synchronizer/demodulator 258that determines, from the data stream, information 260 derived from theradio signals. For example, the demodulator 258 includes one or more ofa symbol timing tracking loop, a carrier tracking loop, and a symbolvalue estimator that can derive the information from the data stream.The demodulator 258 determines one or more of a time instant of theradio signal received at the sensing device 202, a frequency of theradio signal, a rate of the received signal (e.g., a symbol rate), ameasure of signal fidelity (e.g., a signal to noise ratio, receivedsignal strength, or a bit error rate), and the information bits or voicecontents transmitted from the emitter.

In some implementations, the information 260 derived from the radiosignals may include signal and channel parameters such as the time ofarrival at the sensing device 202, a propagation time from the emitter212 to the sensing device 202, a frequency of arrival at the sensingdevice 202, Doppler offset, estimated velocity vectors corresponding tothe radio signals, etc. In some other implementations, the information260 may include information bits or voice contents obtained from thereceived signals. In some cases, the information 260 may also includeprior knowledge about the radio signals such as a type of signal and asignal parameter that defines one or more features of the radio signals(e.g., a pulse shape that envelops the radio signals). Thus, theinformation 260 describes an arrival mode (e.g., channel stateinformation) of the radio signals as well as data description and/orcontents (e.g., information bits, modulation parameters, a pulse shape,an arrival time, an arrival frequency, symbol rate, impulse response,other signal parameters, etc.). The channel state information mayinclude a channel impulse response related to a noise level, a timedelay, an attenuation level of the emission during the propagationthrough the radio channel 220.

The sensing device 202 may further include a remodulator 262 thatgenerates a reconstructed signal corresponding to the radio signalsusing the information 260 determined by the demodulator 258 such ascontents data, signal and channel parameters, and channel stateinformation (e.g., a precise time of arrival, a frequency of arrival, achannel impulse response). For example, the remodulator 262 performsreconstruction of what the received signal should have looked like as atime-domain signal using the information 260. The reconstructed signalsmay be very similar to the received radio signal in a frequency domainas well as in the time domain. In some cases, the reconstructed signalmay be a near-perfect match to the received radio signal, whichminimizes a mean squared value or another cost function between thereconstructed signal and the raw uncorrected arriving signal emission atthe sensing device 202, for instance.

The sensing device 202 further includes a matched filter 264 thatperforms a correlation (e.g., a cross-correlation, or other costfunction computation) with the reconstructed signals and the receivedradio signals to produce a precise correlation peak estimate for theradio signals. Based on a degree of matching between the reconstructedsignals and the received radio signals, the matched filter may estimateor refine a precise correlation peak, while the demodulator 285 oranother reception/synchronization algorithm, described above, determinesa rough estimate of the time instant and the frequency of the receivedradio signals. Based on the results from the matched filter 264, thefine time & frequency estimator 266 determines a high accuracy estimateof time and frequency of the radio signals received at the sensingdevice 202. Alternatively or in addition, in some implementations, thesensing device 202 includes a detection algorithm or detection methodthat is different from the matched filter 264 and that minimizes a costfunction such as a mean squared value. For example, the detection methodmay include determining a value within a predetermined range from aminimum value or a maximum value of a cost-surface of the cost function.

A metadata data structure (or simply metadata 268) describes when andhow a radio emission arrived at a sensing device and what data andparameters were included in such a radio emission. For example, themetadata 268 includes the estimated values obtained by the time &frequency estimator 266. In some examples, the metadata 268 includes thefine time estimate and the fine frequency estimate at assigned addressesor field names such as Time of arrival (TOA) and Frequency of arrival(FOA) in the metadata data structure. In some instances, the metadata268 may include fields from the emission data or header fields, forexample for AIS emissions this could include ship identificationnumbers, radio call signs, vessel names, or other received valuesencoded or derived from the emissions. For other types of emissions,other similar relevant fields may be alternatively included. In someimplementations, the metadata 268 may be a compressed as JavaScriptObject Notation (JSON) string-encoded items, keys and/or values, or as acompact binary encoding of the corresponding values, for example, usingprotocol buffers or protobufs, or using a C programming language-stylenumerical encoding method (e.g., a C “struct” data structure). Table 1below shows one example of the metadata structure. Although, the examplemetadata structure shown in Table 1 includes seven data field names anddata types (e.g., using a suitable encoding, such as using C programminglanguage encoding), the metadata may include different field names anddata types and different numbers of field names and data types.

TABLE 1 An example metadata structure Data Type (bytes) Field Name Int32(4) Checksum 32bit float32 (4) Signal to noise ratio float64 (8) Signalfrequency of arrival Int64 (8) Emission Integer Time in seconds float64(8) Emission time in fractional seconds bytes [256] (256) Buffer ofemission data dictionary (variable) Other annotations describingemission

The system 200 a includes an information combining node 240 and acommunications bus 230 to transmit and/or receive the metadatacorresponding to radio signals. For example, the metadata descriptive ofthe radio signals are transmitted over a communications bus 230 thatincludes a band of frequencies such as a VHF-band, a UHF-band, anS-band, a Ku-band, a Ka-band, an X-band, or other band of radiofrequencies that are configured to carry a digital radio signal. Theinformation combining node 240 (e.g., a ground station or anothersatellite) receives the metadata through the communications bus 230. Insome implementations, the system 200 a may include one or moreinformation combining nodes 240 such as a data center, a ship controlcenter, or a satellite control center, a space station, or othersatellites. The information combining node 240 receives metadata fromtwo or more sensing devices included in a distributed system andcombines the received metadata to determine or estimate a location ofthe radio emitter 212.

FIG. 2B illustrates a block diagram of an example of a distributedmulti-sensor system 200 b that includes two or more sensing devices 202a, 202 b, and 202 c configured to receive radio emissions from a radioemitter 212 through multiple radio channels 220 a, 220 b, and 220 c. Insome implementations, one or more of the sensing devices 202 a, 202 b,and 202 c correspond to one or more of the sensing devices 102, 104, and106 in FIG. 1 or the sensing device 202 in FIG. 2A. Although threesensing devices 202 a, 202 b, and 202 c are shown in FIG. 2B, in someimplementations the system 200 b includes a different number of sensingdevices. For example, the system 100 can include two sensing devices(e.g., 202 a and 202 b) or four or more sensing devices.

The system 200 b further includes an information combining node 240 thatreceives metadata 268 a, 268 b, 268 c, or metadata 270 through acommunications bus 280. In some cases, the metadata 270 may include allor a portion of the metadata 268 a, 268 b, and 268 c. For example, theinformation combining node 240 may be able to determine a location ofthe emitter based on the metadata 270 received from two sensing devices(e.g., sensing devices 202 a and 202 b) within a certain accuracy level.In such cases, the information combining node 240 may receive themetadata from the two sensing devices 202 a and 202 b to determine thelocation of the emitter 212. The information combining node 240aggregates the received metadata 270 to perform estimation of a locationof the emitter 212. The information combining node 240 may correspond tothe information combining node 140 in FIG. 1 or the informationcombining node 240 in FIG. 2A. In some examples, one or more of themetadata 268 a, 268 b, and 268 c, or 270 may correspond to the metadata268 in FIG. 2A.

In some implementations, each of the multiple sensing devices 202 a, 202b, and 202 c receives an emission (e.g., a radio frequency signal) froma radio emitter 212 over a plurality of radio channels (e.g., paths) 220a, 220 b, and 220 b. In some examples, each sensing device receives theemission over a single channel mode. For instance, the sensing device202 a receives the emission through the radio channel 220 a, the sensingdevice 202 b receives the emission through the radio channel 220 b, andthe sensing device 202 c receives the emission through the radio channel220 c.

In other implementations, a sensing device may possibly receive theemission propagated through multiple channels that are different fromone another. For example, if a reflection causes two or more copies ofan emission, a sensing device (e.g., sensing device 202 a) receives thetwo or more copies of an emission through two or more distinct paths(e.g., radio channels 220 a, 220 b, and 220 c). Since each of the radiochannels 220 a, 220 b, and 220 c may have different propagationcharacteristics such as a type of a medium, a density of the medium, atemperature in the path, a noise level, or obstacles, the radio signalsreceived at the sensing devices 202 a, 202 b, and 202 c may correspondto different values of parameters in terms of a time delay, a frequencyoffset, a noise level, or other distortions. In such implementations,the metadata 268 a, 268 b, and 268 c may include different data valuesfrom each other for the emission emitted from the same emitter 212 inwhich the information combining node 240 may be able to estimate thelocation of the emitter 212 based on one or more of the metadata 268 a,268 b, 268 c, and 270.

FIG. 3 illustrates a block diagram of an example of an informationcombining node 340 that determines a location of an emitter based on oneor more of metadata 360 a, 360 b, and 360 c corresponding to emissionfrom the emitter. In some implementations, the information combiningnode 340 corresponds to the information combining node 140 in FIG. 1 orthe information combining node 240 in FIG. 2A or FIG. 2B. For example,the information combining node 340 receives the metadata 360 a, 360 b,or 360 c for one or more emissions through the communications bus 330.In some implementations, the communications bus 330 corresponds to thecommunications links 134 and 136 in FIG. 1, the communications bus 230in FIG. 2A, or the communications bus 280 in FIG. 2B. The informationcombining node 340 includes one or more processors 342 that performoperations for location estimation, and one or more memory devices 350that store metadata or location estimation results (e.g., history oflocation of an emitter) based on the metadata. In some implementations,the information combining node 340 may include multiple processors,which are collectively indicated as the one or more processor 342.

The one or more processors 342 of the information combining node 340perform processes to determine a location of an emitter. For example,the one or more processors 342 perform a time & frequency distancecalculation process 344 (e.g., computing the differences between timeand frequency of multiple emissions and corresponding geometry or othereffects), combining and object estimation process 346, and location andbehavior estimation process 348. The one or more processors 342 receivetwo or more of the metadata 360 a, 360 b, and 360 c, and telemetryinformation 352 about the respective sensing devices that sent themetadata 360 a, 360 b, and 360 c, respectively. For instance, thetelemetry information 352 includes trajectory information of the sensingdevices such as a position, a velocity, or a travel time or schedule ofeach sensing device. In some implementations, the telemetry informationmay be included in the respective metadata. In other implementations,the telemetry information may be stored at the information combiningnode, e.g., at the memory 350. In some cases, the sensing devices maytransmit the telemetry information over the communications bus 330 orother communications links along with the metadata. In other cases, thesensing devices may transmit the telemetry information independent oftransmission of the metadata.

In some implementations, the one or more processors 342 performs thetime and frequency distance calculation process 344 to determine arelationship between the metadata 360 a, 360 b, and 360 c. For example,the one or more processors 342 determine a distance metric or anothercost function corresponding to the metadata 360 a, 360 b, and 360 cusing the TOA data included in the metadata 360 a, 360 b, and 360 c andposition information included in the telemetry information of thecorresponding sensing devices. For example, if the TOA in the metadata360 a and the TOA in the metadata 360 b are equal to or similar to eachother, a candidate location of the emitter may be at a position betweenpositions of two sensing devices that sent the metadata 360 a and themetadata 360 b. The telemetry information such as velocities of thesensing devices may improve estimation of the candidate location.

In some examples, the one or more processor 324 may determine a distancemetric or another cost function using the FOA data included in themetadata 360 a, 360 b, and 360 c and velocity information in thetelemetry information of the corresponding sensing devices. Forinstance, the FOA in the metadata 360 a may be different from the FOA inthe metadata 360 b due to Doppler offset if the corresponding sensingdevices move in different velocities.

The one or more processors 342, at the combining process and objectestimation process 346, identify an object (e.g., candidate emitter(s))corresponding to the metadata 360 a, 360 b, and 360 c. In someimplementations, the one or more processors 342 may identify a candidateemitter corresponding to the radio signals based on the telemetryinformation of one or more of sensing devices, the metadata, or therelationship. In some implementations, the one or more processors 342may also utilize information about candidate emitters.

For example, the information regarding the candidate emitters includesat least one of a type of the candidate emitter, a history of locationsof the candidate emitter, a travel schedule of the candidate emitter, afrequency band of an emission from the candidate emitter, a frequencyoffset of the emission, a pulse shape of the emission, modulationparameters of the emission, or an acoustic content included in theemission. As one example of the information regarding candidateemitters, AIS information of a vessel includes a unique identification,position, course, speed, and frequency band of the vessel, which can beutilized to identify a candidate emitter or vessel. In someimplementations, the one or more processors 342 determine one or morecandidate emitters based on the combining and object estimation 346process.

The one or more processors 342 performs the location and behaviorestimation process 348 to determine best estimates of the candidatelocation and the candidate emitter corresponding to the metadata. Forexample, the one or more processors 342 may utilize an output from thecombining and object estimation process 346, which includes one or moreof estimated emitters, estimated locations of emitters during emissions,a corresponding time and contents of the emissions. In the location andbehavior estimation process 348, the one or more processors 342determine a best estimate as to the location of the emission from amongthe estimated locations and a best estimate as to the object (e.g., theemitter) corresponding to the emission from among the estimatedemitters.

In some implementations, the one or more processors 342 determineinformation about the current behavior of the emitter. For instance, theone or more processors 342 may determine, based on the best estimatesfor the candidate location and candidate emitter, whether the candidateemitter (e.g., a vessel or aircraft) is in a restricted area or performsa restricted activity in an area monitored by the sensing devices. Insome examples, the one or more processors 342 may also analyze theinformation bits or acoustic/voice contents included in the metadata todetermine the behavior of the emitter.

In some implementations, the one or more processors 342 may utilizeother information 354 about the emitter and be configured to performoperations corresponding to one or more of the processes 344, 346, or348. For example, other information 354 may include prior knowledgeabout the emitter such as a history of locations or prior behaviors ofthe emitter, expected locations of the emitter based on prior emissions,locations of other emitters, weather around the estimated locations,surrounding environments around the estimated locations, restricted areainformation, etc. This information may be provided by one or more of thesensing devices in the same distributed system, other sensing devices inanother distributed system, a third party information repository, or aninternet source that specifies a type of the candidate emitter, a travelschedule of the candidate emitter, or a frequency band of an emissionfrom the candidate emitter, for instance.

In some implementations, the information combining node 340 includes amemory 350 that stores results from the location & behavior estimationprocess 348. In some implementations, alternatively or in addition, theresults are transmitted via a downstream communications bus 356 to otherinformation processing nodes or objects (e.g., customers, controlcenters, or other devices) that use information regarding the emitter, acurrent location of the emitter, and a behavior of the emitter.

In some implementations, the one or more processors 342 executeinstructions that are stored in the memory 350. The instructions includeoperations corresponding to performing spatial localization computationsand/or controlling various sensing devices (e.g., one or more of sensingdevices 102, 104, and 106) to identify emitter locations based onmetadata received from the sensing devices. These operations include,among other things, processing the metadata received from the sensingdevices into estimates of locations, users, timing, and other usefulsignal metrics. The one or more processors 342 output the estimates to auser or administrator, e.g., through a display coupled to theinformation combining node 340, and/or transmit the estimates to otherdevices or databases, e.g., other information combining nodes, receiverstations, storage devices, or network nodes.

The memory 350 stores instructions that are executed by the processor(s)342, as described above. The memory 350 also stores the metadata thatare received from one or more sensing devices, and/or results of thecomputations that are performed by the information combining node 340.In some implementations, the memory 350 stores additional information,such as application logs, process tasking information, planning andanalysis information, among other things.

In some implementations, the memory 350 includes one or more of randomaccess memory (RAM), various types of read-only memory (ROM), and otherlong-term storage memory, such as non-volatile flash memory, hard drivestorage, storage disks, or other suitable storage media.

In some implementations, the one or more processors 342 include anembedded microprocessor or field-programmable gate array(s) (FPGA)digital logic subsystem that can improve performance for estimation ofthe emitter, a location of the emitter, and a behavior of the emitterbased on the metadata and knowledge about the emitter. In some examples,the one or more processors 342 include application-specific integratedcircuits (ASIC) that can process the metadata received from multiplesensing devices of the distributed system. In other implementations, theone or more processors 342 may include general purpose multiprocessors.For example, the one or more processors 342 may include digital signalprocessing (DSP) features, general-purpose pre-processor(s) (GPP), orgeneral-purpose graphics processing unit(s) (GPGPU).

In some implementations, the one or more processors 342 include parallelprocessing capabilities, e.g., the one or more processors include GPUhardware. In such cases, the instructions corresponding to operationsfor the spatial localization based on metadata are customized such thatthey are executed efficiently using the parallel processors 342. Thisleads to improvement in the functioning of the information combiningnode 340, e.g., leading to faster execution, lower expenditure ofenergy, and/or lower heat generation. In this manner, the parallelexecution of the instructions corresponding to operations for thespatial localization based on metadata improves the functionality of theinformation combining node 340. This is useful, for example, when theinformation combining node 340 processes a large amount of metadata,e.g., covering a large area and/or multiple areas and that are receivedfrom a plurality of sensing devices.

In some implementations, the information combining node 340 includes onecommunications transponder. In other implementations, the informationcombining 340 includes multiple communications transponders. In someimplementations, the communications transponder(s) includedownlink/uplink communications transponder(s), which are used tocommunicate with the sensing devices, e.g., to transmit command andcontrol instructions, receive emitter signals obtained by the sensors onthe sensing devices, or processed information about these signals suchas metadata that are generated by one or more sensing devices. In someimplementations, the information combining node 340 uses thedownlink/uplink communications transponders to send updates to software(e.g., updates to the algorithms) stored in sensing device memory.

In some implementations, the information combining node 340 includes onenetwork interface. In other implementations, the information combiningnode 340 includes multiple network interfaces. The information combiningnode 340 connects to one or more terrestrial networks, e.g., using localarea network (LAN) or wide area network (WAN) connections, through thenetwork interfaces. The information combining node 340 communicates withother transceiver/receiver stations, satellite ground stations, or othernetwork devices on the ground, or to remote datacenters, through theterrestrial or other networks that are accessed over the networkinterfaces. In this manner, in some implementations, the processors 342communicate the computed estimates, which are noted above, to othernetwork devices or receiver stations through the network interfaces.

FIG. 4 illustrates an example of realization of a distributed system 400including a communications bus between sensing devices 400A, 400B, 400C,and 400D and between a sensing device and an information combining node441. In this example, the sensing devices or sensors are satellites, andthe communications bus includes several possible types of radiocommunications links or optical communications links 431, 432, 433, 434,and 435. The system 400 includes one or more ground stations 437A and437B that are connected to the information combining node 441.

In some implementations, the system 400 includes a communicationssatellite 460 that is operated by the same satellite operator as one ormore of the sensing devices 400A, 400B, 400C, and 400D. In someimplementations, the communications satellite is operated by a differentsatellite operator or commercially operated. The communicationssatellite 460 may move in a similar orbit as one or more of the sensingdevices 400A, 400B, 400C, and 400D, or may move in a different orbit.For example, the communications satellite 460 may move along an orbitthat is located at a higher or lower distance from ground than one ormore of the sensing devices 400A, 400B, 400C, and 400D. One or more ofthe sensing devices 400A, 400B, 400C, and 400D may communicate with thecommunications satellite 460 through a communications link 434 totransmit metadata determined at the respective sensing devices (e.g.,sensing device 400B). The communications satellite 460 transmitsinformation (e.g., the metadata) to one or more of ground stations(e.g., ground station 437A) over radio or optical communications link435.

The sensing devices 400A, 400B, 400C, and 400D transmit information(e.g., metadata) as described above via a communications bus to aninformation combining node 441. For example, the sensing devices 400Aand 400C, respectively, transmit information via a direct downlink radioor optical link 431 and 432 to ground based antennas 436A and 436B ofground stations 437A and 437B. One or both of the ground stations 437Aand 437B receive information such as metadata from sensing devices orcommunications satellite 460 and process the received metadata. In someimplementations, the ground stations 437A and 437B transmit the receivedmetadata or the processed information to another ground station througha communications link 438A, or to an information combining node 441through a communications link 438B.

In some implementations, metadata generated by one sensing device istransferred through a communications link connected to another sensingdevice. For example, the sensing device 400D transmits information overa radio or optical cross-link 433 to the sensing device 400C, which thentransmits the information over a radio or optical communications link432 to the ground (e.g., ground station 437B).

In some implementations, when metadata information reaches a groundantenna 436A or 436B and a corresponding ground station 437A or 437B,the metadata information is transmitted to the information combiningnode 441. The information combining node 441 aggregates the metadatainformation from all or a portion of sensing devices corresponding tomultiple observations of emissions. In some implementations, themetadata transmission to the information combining node 441 happensimmediately as the metadata information is received at a ground antenna436A or 436B and a corresponding ground station 437A or 437B. In someother implementations, for one or more ground antennas 436A and 436B andthe corresponding ground stations 437A and 437B, the transmission ofmetadata to the information combining node 441 takes place after afinite delay following receipt of the metadata at the ground antenna436A or 436B and the corresponding ground station 437A or 437B. In someimplementations, the combining takes place after a finite delay prior totransmission from the sensor to the ground station. For example, theremay be a delay before the sensing device 400A, 400B, 400C, or 400D canclose a communications link (e.g., 431, 432, 433, or 435) and transmitmetadata to the ground station 437A or 437B, where the metadata may berelayed to the combining node 441.

In some implementations, different ground antennas 436A and 436B, andcorresponding ground stations 437A and 437B, transmit the same metadatareceived at the respective locations to the information combining node441 at different times. For instance, the ground station 437A maytransmit the metadata to the information combining node 441 at a firsttime instant, and the ground station 437B may transmit the metadata tothe information combining node 441 at a second time instant that isgreater or less than the first time instant. In some implementations, aground station (e.g., ground station 437B) receives metadata fromanother ground station (e.g., ground station 437A) through acommunications link (e.g., 438A) and transmits the received metadata tothe information combining node 441 through a communications link (e.g.,438B).

In some implementations, the information combining node 441 isco-located at a ground station 437A or 437B. In such implementations,one or more of the ground stations 437A and 437B include componentscorresponding to those of the information combining node 441 such as oneor more processors, a memory device, and one or more communicationstransponders. In some implementations, the information combining node441 is co-located on one of the sensing devices 400A, 400B, 400C, or400D. In such implementations, one or more of the sensing devices 400A,400B, 400C, or 400D include components corresponding to those of theinformation combining node 441 such as one or more processors, a memorydevice, and one or more communications transponders.

FIG. 5 illustrates an example of a process 500 for generating metadatabased on radio signals and determining a candidate location from whichthe radio signals were emitted, according to one or moreimplementations. The process 500 can be performed by components of thesystems 200 a, 200 b, 300, or any suitable combination thereof. Forexample, the process 500 can be performed by two or more of the sensingdevices 202, 202 a, 202 b, or 202 c, and the information combining node240, or by a suitable combination of the sensing devices and theinformation combining node 240. Accordingly, the following sectionsdescribe the process 500 with respect to the system 200 a, 200 b, or300. For example, each sensing device 202 a and 202 b of the system 200b includes corresponding components in the sensing device 202 of thesystem 200 a. However, the process 500 also can be performed by othersuitable devices or systems.

In some implementations, the process 500 is performed by one or moreprocessors associated with the respective device(s) performing theprocess 500. For example, the sensing device 202, or the sensing devices202 a, 202 b, or 202 c, can perform the process 500 by executinginstructions corresponding to the process 500 that are stored in memorycoupled to the respective sensing device. The instructions are executedby one or more processors coupled to the respective sensing device.Additionally or alternatively, in some implementations, the informationcombining node 240 can perform the process 500 by executing instructionscorresponding to the process 500 that are stored in memory coupled tothe information combining node 240. The instructions are executed by oneor more processors coupled to the information combining node 240.

In some implementations, the process 500 is performed by a plurality ofsensing devices, e.g., M sensing devices, where M is an integer greaterthan 2. For example, the process 500 can be performed by the sensingdevices 202 a, 202 b and 202 c, and additional sensing devices in thesystem 200 b.

At 502, the system 200 b obtains, from a first sensing device, firstinformation corresponding to a first radio signal received at the firstsensing device from a candidate location. For example, the sensingdevice 202 a receives a first radio signal from the emittercorresponding to the candidate location. In some examples, the firstradio signal is emitted through a radio channel 220 a and receivedthrough an antenna 252 of the first sensing device 202 a. In someimplementations, the received radio signal is sent to a processor onboard of the sensing device 202 a.

At 504, the system 200 b determines a first reconstructed signalcorresponding to the first radio signal based on the first information.For example, a remodulator 262 of the first sensing device 202 agenerates a first reconstructed signal corresponding to the first radiosignal using information such as contents data, signal and channelparameters, and the channel state information of the first radio signal.In some implementations, the information, for generating the firstreconstructed signal, is determined by one or more of a digitizer 254, asignal detector 256, or a demodulator 258 of the first sensing device202 a. In some examples, the signal detector 256 and the demodulator 258utilized a digitized data stream generated by the digitizer 254corresponding to the first radio signal.

At 506, the system 200 b determines at least one of a firsttime-estimate or a first frequency-estimate based correlation betweenthe first radio signal and the first reconstructed signal. For example,the sensing device 202 a computes a correlation (e.g., across-correlation) with the first reconstructed signal and the receivedradio signal to produce a precise correlation peak estimate for thefirst radio signal. In some examples, the sensing device 202 a utilizesa matched filter 264 to compute the correlation. In someimplementations, the fine time & frequency estimator 266 determines,based on results from the matched filter 264, a high accuracy estimateof time and frequency of the first radio signal received at the sensingdevice 202 a. In some implementations, the first time-estimate or thefirst frequency-estimate is determined based on one or more costmetrics, different from the correlation described above, between thefirst radio signal and the first reconstructed signal.

At 508, the system 200 b determines first metadata corresponding to thefirst radio signal based on at least one of the first information, thefirst time-estimate, or the first frequency-estimate. For example, thesystem 200 b includes a data structure of the metadata including one orboth of the first time-estimate and the first frequency-estimate. Insome examples, the data structure may include one or more of thecontents data, signal and channel parameters, and channel stateinformation, which correspond to the information for generating thefirst reconstructed signal. In some implementations, the data structureof metadata may include a signal to noise value. In some examples, themetadata may be stored in a memory of the sensing device 202 a ortransmitted to downstream processes.

At 510, the system 200 b obtains, from a second sensing device, secondinformation corresponding to a second radio signal received at thesecond sensing device from the candidate location. For example, thesensing device 202 b receives a second radio signal from the emittercorresponding to the candidate location. In some examples, the secondradio signal is emitted through a radio channel 220 b and receivedthrough an antenna 252 of the second sensing device 202 b. In someimplementations, the received radio signal is sent to a processor onboard of the sensing device 202 b.

At 512, the system 200 b determines a second reconstructed signalcorresponding to the second radio signal based on the secondinformation. For example, a remodulator 262 of the second sensing device202 b generates a second reconstructed signal corresponding to thesecond radio signal using information such as contents data, signal andchannel parameters, and the channel state information of the first radiosignal. In some implementations, the information, for generating thesecond reconstructed signal, is determined by one or more of a digitizer254, a signal detector 256, or a demodulator 258 of the second sensingdevice 202 b. In some examples, the signal detector 256 and thedemodulator 258 utilized a digitized data stream generated by thedigitizer 254 corresponding to the second radio signal.

At 514, the system 200 b determines at least one of a secondtime-estimate or a second frequency-estimate based a correlation betweenthe second radio signal and the second reconstructed signal. Forexample, the sensing device 202 b computes a correlation (e.g., across-correlation) with the second reconstructed signal and the receivedradio signal to produce a precise correlation peak estimate for thesecond radio signal. In some examples, the sensing device 202 b utilizesa matched filter 264 to compute the correlation. In someimplementations, the fine time & frequency estimator 266 determines,based on results from the matched filter 264 or another similardetector, a high accuracy estimate of time and frequency of the secondradio signal received at the sensing device 202 b. Alternatively or inaddition, in some implementations, the second time-estimate or thesecond frequency-estimate is determined based on one or more costmetrics, different from the correlation described above, between thesecond radio signal and the second reconstructed signal.

At 516, the system 200 b determines second metadata corresponding to thesecond radio signal based on at least one of the second information, thesecond time-estimate, or the second frequency-estimate. For example, thesystem 200 b includes a data structure of the metadata including one orboth of the second time-estimate and the second frequency-estimate. Insome examples, the data structure may include one or more of thecontents data, signal and channel parameters, and channel stateinformation, which correspond to the information for generating thesecond reconstructed signal. In some implementations, the data structureof metadata may include a signal to noise value. In some examples, themetadata may be stored in a memory of the sensing device 202 b ortransmitted to downstream processes.

At 518, the system 200 b transmits at least one of the first metadata orthe second metadata to an information combining node. For example, thefirst sensing device 202 a transmits the first metadata to aninformation combining node 240, and the second sensing device 202 btransmits the second metadata to the information combining node 240. Insome implementations, one or both of the first and second sensingdevices 202 a and 202 b may transmit the respective metadata to anothersensing device that transmits the respective metadata to the informationcombining node 240. In some cases, one of the first sensing device 202a, the second sensing device 202 b, or another sensing device maycorrespond to the information combining node 240. For instance, thesecond sensing device 202 b receives the first metadata from the firstsensing device 202 a and performs processes corresponding to theinformation combining node 240.

At 520, the system 200 b obtains, from the information combining node,at least one of the first metadata or the second metadata. For example,the information combining node 240 obtains, through the communicationbus 280, the first metadata from the first sensing device 202 a, thesecond metadata from the second sensing device 202 b, or both. Inexamples where one or more of the first and second metadata weretransmitted to an intermediate sensing device (e.g., a third partysatellite), the information combining node 240 may obtain the firstmetadata or the second metadata from the intermediate sensing device.

At 522, referring to FIG. 3, the system 300 determines a relationshipbetween the first metadata and the second metadata. For example, one ormore processors 342 of the information combining node 340 may determinea distance metric corresponding to the metadata 360 a and 360 b usingthe TOA data included in the metadata 360 a and 360 b. For example, thedistance metric may be a temporal distance value corresponding to a timedifference between the TOA values of the respective metadata. In someimplementations, the one or more processors 342 may determine a distancemetric corresponding to the metadata 360 a and 360 b using the FOA dataincluded in the respective metadata. For example, the distance metricmay be a spectral distance value corresponding to a frequency differencebetween the FOA values of the respective metadata.

At 524, the system 300 determines the candidate location based on thefirst metadata, the second metadata, and the relationship between thefirst metadata and the second metadata. For example, the one or moreprocessor 342 determine the candidate location based on results of thetime & frequency distance calculation process 344. In some examples, thecandidate location of the emitter may be determined based on a ratio ofthe TOA included in the first metadata 360 a and the TOA included in thesecond metadata 360 b. In some examples, the system 300 may utilize oneor more of additional metadata (e.g., metadata 360 c), additionalinformation 354 about the emitter, or telemetry information 352 such asvelocities or trajectories of the sensing devices that transmitted therespective metadata to improve estimation of the candidate locationbased on the first metadata 360 a and the second metadata 360 b.

FIG. 6 illustrates an example of a process 600 for identifying acandidate emitter based on metadata received at an information combiningnode, according to one or more implementations. The process 600 can beperformed by components of the system 300. For example, the informationcombining node 340 can perform the process 600 by executing instructionscorresponding to the process 600 that are stored in memory (e.g., memory350) coupled to the information combining node 340. The instructions areexecuted by one or more processors 342 coupled to the informationcombining node 340.

At 602, the system 300 obtains information regarding the candidateemitter. For example, one or more processors 342 of the informationcombining node 340 obtains the information regarding the candidateemitter from one or more of the first metadata 360 a, the secondmetadata 360 b. In some examples, the one or more processors 342 mayobtain the information regarding the candidate emitter before receivingthe first metadata 360 a or the second metadata 360 b. In otherexamples, the one or more processors 342 may obtain the informationafter receipt of the first metadata 360 a or the second metadata 360 b,for example, by searching an internet source or database that specifiesa type of the candidate emitter, a travel schedule of the candidateemitter, or a frequency band of an emission from the candidate emitter.

At 604, the system 300 determines whether metadata correspond to theinformation regarding the candidate emitter. For example, the one ormore processors 342 determines whether one or both of the first metadata360 a and the second metadata 360 b corresponds to the informationregarding the candidate emitter. For instance, the one or moreprocessors 342 compares signal parameters such as frequency ranges ormodulation parameters (e.g., symbol rates, constellations, or shapes,among others) included the metadata 360 a and 360 b with correspondinginformation included in the information regarding the candidate emitter.In some cases, contents data included in the metadata 360 a and 360 bmay be utilized to determine whether the metadata correspond to theinformation regarding the candidate emitter. For example, the one ormore processors 342 may compare voice or acoustic contents included inthe metadata 360 a and 360 b with the information regarding thecandidate emitter that includes voice or other acoustic contents ofvarious emitters.

At 606, the system 300 identifies a candidate emitter based on adetermination that the metadata corresponds to the information regardingthe candidate emitter. For example, the one or more processors 342determines a candidate emitter based on a determination that one or bothof the first metadata 360 a and the second metadata 360 b corresponds tothe information regarding the candidate emitter. In some examples, thecandidate emitter may include a plurality of candidate emitters. Forexample, the first metadata data 360 a may correspond to a first portionof the plurality of candidate emitters, and the second metadata 360 bmay corresponds to a second portion of the plurality of candidateemitters. In some cases, identifying a candidate emitter may includeidentifying one or more common candidate emitters from the first andsecond portions of the plurality of candidate emitters. In someexamples, the plurality of candidate emitters may include a relevancescore corresponding to results of comparison between the metadata 360a/360 b with the information regarding the candidate emitter. In theseexamples, identifying a candidate emitter may include identifying one ormore candidate emitters based on the relevance score (e.g., 1^(st)highest score emitter, five highest score emitters, etc.).

The disclosed and other examples can be implemented as one or morecomputer program products, for example, one or more modules of computerprogram instructions encoded on a computer readable medium for executionby, or to control the operation of, data processing apparatus. Theimplementations can include single or distributed processing ofalgorithms. The computer readable medium can be a machine-readablestorage device, a machine-readable storage substrate, a memory device,or a combination of one or more them. The term “data processingapparatus” encompasses all apparatus, devices, and machines forprocessing data, including by way of example a programmable processor, acomputer, or multiple processors or computers. The apparatus caninclude, in addition to hardware, code that creates an executionenvironment for the computer program in question, e.g., code thatconstitutes processor firmware, a protocol stack, a database managementsystem, an operating system, or a combination of one or more of them.

A system may encompass all apparatus, devices, and machines forprocessing data, including by way of example a programmable processor, acomputer, or multiple processors or computers. A system can include, inaddition to hardware, code that creates an execution environment for thecomputer program in question, e.g., code that constitutes processorfirmware, a protocol stack, a database management system, an operatingsystem, or a combination of one or more of them.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, and the computerprogram can be deployed in any form, including as a standalone programor as a module, component, subroutine, or other unit suitable for use ina computing environment. A computer program does not necessarilycorrespond to a file in a file system. A program can be stored in aportion of a file that holds other programs or data (e.g., one or morescripts stored in a markup language document), in a single filededicated to the program in question, or in multiple coordinated files(e.g., files that store one or more modules, sub programs, or portionsof code). A computer program can be deployed for execution on onecomputer or on multiple computers that are located at one site ordistributed across multiple sites and interconnected by a communicationsnetwork.

The processes and logic flows described in this document can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random access memory or both. The essential elements of a computer caninclude a processor for performing instructions and one or more memorydevices for storing instructions and data. Generally, a computer canalso include, or be operatively coupled to receive data from or transferdata to, or both, one or more mass storage devices for storing data,e.g., magnetic, magneto optical disks, or optical disks. However, acomputer need not have such devices. Computer readable media suitablefor storing computer program instructions and data can include all formsof nonvolatile memory, media and memory devices, including by way ofexample semiconductor memory devices, e.g., EPROM, EEPROM, and flashmemory devices; magnetic disks, e.g., internal hard disks or removabledisks; magneto optical disks; and CD ROM and DVD-ROM disks. Theprocessor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry.

While this document may describe many specifics, these should not beconstrued as limitations on the scope of an invention that is claimed orof what may be claimed, but rather as descriptions of features specificto particular embodiments. Certain features that are described in thisdocument in the context of separate embodiments can also be implementedin combination in a single embodiment. Conversely, various features thatare described in the context of a single embodiment can also beimplemented in multiple embodiments separately or in any suitablesub-combination. Moreover, although features may be described above asacting in certain combinations and even initially claimed as such, oneor more features from a claimed combination in some cases can be excisedfrom the combination, and the claimed combination may be directed to asub-combination or a variation of a sub-combination. Similarly, whileoperations are depicted in the drawings in a particular order, thisshould not be understood as requiring that such operations be performedin the particular order shown or in sequential order, or that allillustrated operations be performed, to achieve desirable results.

Only a few examples and implementations are disclosed. Variations,modifications, and enhancements to the described examples andimplementations and other implementations can be made based on what isdisclosed.

What is claimed is:
 1. A method comprising: obtaining, from a firstsensing device, first information corresponding to a first radio signalreceived at the first sensing device from a candidate location;determining a first reconstructed signal corresponding to the firstradio signal based on the first information; determining at least one ofa first time-estimate or a first frequency-estimate based on acorrelation between the first radio signal and the first reconstructedsignal; determining first metadata corresponding to the first radiosignal based on at least one of the first information, the firsttime-estimate, or the first frequency-estimate; obtaining, from a secondsensing device, second information corresponding to a second radiosignal received at the second sensing device from the candidatelocation; determining a second reconstructed signal corresponding to thesecond radio signal based on the second information; determining atleast one of a second time-estimate or a second frequency-estimate basedon correlation between the second radio signal and the secondreconstructed signal; determining second metadata corresponding to thesecond radio signal based on at least one of the second information, thesecond time-estimate, or the second frequency-estimate; transmitting atleast one of the first metadata or the second metadata to an informationcombining node; obtaining, from the information combining node, at leastone of the first metadata or the second metadata; determining arelationship between the first metadata and the second metadata; anddetermining the candidate location based on the first metadata, thesecond metadata, and the relationship between the first metadata and thesecond metadata, wherein transmitting at least one of the first metadataor the second metadata to the information combining node comprisesrestricting transmission of the first radio signal and the second radiosignal to the information combining node based on a bandwidth or storageof the first sensing device, the second sensing device, or theinformation combining node, wherein determining the first reconstructedsignal comprises minimizing a first cost metric corresponding to adifference between the first reconstructed signal and the first radiosignal, and wherein determining the second reconstructed signalcomprises minimizing a second cost metric corresponding to a differencebetween the second reconstructed signal and the second radio signal. 2.The method of claim 1, wherein determining the candidate locationcomprises determining the candidate location based on at least one ofthe first metadata received at the information combining node or thesecond metadata received at the information combining node.
 3. Themethod of claim 1, wherein a bandwidth for transmitting the firstmetadata from the first sensing device is less than a bandwidth fortransmitting the first radio signal from the first sensing device,wherein a bandwidth for transmitting the second metadata from the secondsensing device is less than a bandwidth for transmitting the secondradio signal from the second sensing device, wherein a memory space forstoring the first metadata from the first sensing device is less than amemory space for storing the first radio signal from the first sensingdevice, and wherein a memory space for storing the second metadata fromthe second sensing device is less than a memory space for storing thesecond radio signal from the second sensing device.
 4. The method ofclaim 1, wherein transmitting at least one of the first metadata or thesecond metadata to the information combining node comprises transmittingthe first metadata and the second metadata through a communications buscommunicably coupled to the information combining node.
 5. The method ofclaim 4, wherein the communications bus comprises a band of frequenciesthat includes at least one of a VHF-band, a UHF-band, an S-band, aKu-band, a Ka-band, or an X-band that are configured to carry a radiosignal.
 6. The method of claim 1, wherein obtaining the firstinformation comprises: generating a data stream by digitizing the firstradio signal; and obtaining, from the data stream, information derivedfrom the first radio signal.
 7. The method of claim 6, wherein obtainingthe information derived from the radio first signal comprises obtaining,from the data stream, at least one of a time of arrival of the firstradio signal at the first sensing device, a frequency of the first radiosignal at the time of arrival, a frequency offset associated with thefirst radio signal, a signal to noise ratio associated with the firstradio signal, information bits included in the data stream correspondingto the first radio signal, or a signal parameter that defines one ormore features of the first radio signal.
 8. The method of claim 7,wherein determining the first reconstructed signal comprises determiningthe first reconstructed signal based on at least one of the time ofarrival of the first radio signal at the first sensing device, thefrequency of the first radio signal at the time of arrival, the signalto noise ratio of the first radio signal, the signal parameter thatdefines the one or more features of the first radio signal, theinformation bits included in the first radio signal, or the signalparameter that defines the one or more features of the first radiosignal.
 9. The method of claim 7, wherein determining the first metadatacorresponding to the first radio signal comprises determiningdescriptive information corresponding to at least one of the time ofarrival of the first radio signal at the first sensing device, thefrequency of the first radio signal at the time of arrival, the signalto noise ratio of the first radio signal, the information bits includedin the first radio signal, or the signal parameter that defines the oneor more features of the first radio signal.
 10. The method of claim 1,wherein obtaining the second information comprises: generating a datastream by digitizing the second radio signal; and obtaining, from thedata stream, information derived from the second radio signal.
 11. Themethod of claim 10, wherein obtaining the information derived from thesecond radio signal comprises obtaining, from the data stream, at leastone of a time of arrival of the second radio signal at the secondsensing device, a frequency of the second radio signal at the time ofarrival, a frequency offset associated with the second radio signal, asignal to noise ratio associated with the second radio signal,information bits included in the data stream corresponding to the secondradio signal, or a signal parameter that defines one or more features ofthe second radio signal.
 12. The method of claim 11, wherein determiningthe second reconstructed signal comprises determining the secondreconstructed signal based on at least one of the time of arrival of thesecond radio signal at the second sensing device, the frequency of thesecond radio signal at the time of arrival, the signal to noise ratio ofthe second radio signal, the signal parameter that defines the one ormore features of the second radio signal, the information bits includedin the second radio signal, or the signal parameter that defines the oneor more features of the second radio signal.
 13. The method of claim 11,wherein determining the second metadata corresponding to the secondradio signal comprises determining descriptive information correspondingto at least one of the time of arrival of the second radio signal at thesecond sensing device, the frequency of the second radio signal at thetime of arrival, the signal to noise ratio of the second radio signal,or the information bits included in the data stream corresponding to thesecond radio signal.
 14. The method of claim 1, wherein determining thefirst metadata corresponding to the first radio signal comprisesdetermining descriptive information corresponding to at least one of afirst time of arrival at which the first radio signal arrived at thefirst sensing device, or a first frequency of arrival of the first radiosignal received at the first sensing device at the first time ofarrival, and wherein determining the second metadata corresponding tothe second radio signal comprises determining descriptive informationcorresponding to at least one of a second time of arrival at which thesecond radio signal arrived at the second sensing device, or a secondfrequency of arrival of the second radio signal received at the secondsensing device at the second time of arrival.
 15. The method of claim14, wherein determining the candidate location comprises: obtaininginformation regarding a trajectory of at least one of the first sensingdevice or the second sensing device; and identifying a candidate emittercorresponding to the first radio signal and the second radio signalbased on at least one of the information regarding the trajectory of atleast one of the first sensing device or the second sensing device, therelationship between the first metadata and the second metadata, thefirst metadata, or the second metadata.
 16. The method of claim 15,wherein identifying the candidate emitter comprises: obtaininginformation regarding the candidate emitter; determining whether thefirst metadata or the second metadata corresponds to the informationregarding the candidate emitter; and identifying the candidate emitterbased on a determination that the first metadata or the second metadatacorresponds to the information regarding the candidate emitter, whereindetermining the candidate location further comprises determining thecandidate location from estimated locations corresponding to theinformation regarding the candidate emitter, the trajectory of at leastone of the first sensing device or the second sensing device, therelationship between the first metadata and the second metadata, thefirst metadata, and the second metadata.
 17. The method of claim 16,wherein the information regarding the candidate emitter includes atleast one of a type of the candidate emitter, a history of locations ofthe candidate emitter, a travel schedule of the candidate emitter, afrequency band of an emission from the candidate emitter, a frequency ofthe emission, a frequency offset of the emission, a pulse shape of theemission, a modulation parameter of the emission, or an acoustic orvoice content included in the emission.
 18. The method of claim 16,wherein obtaining the information regarding the candidate emittercomprises obtaining the information regarding the candidate emitter fromat least one of the first metadata, the second metadata, the firstsensing device, the second sensing device, another sensing device, aninformation repository, or an internet source that specifies a type ofthe candidate emitter, a travel schedule of the candidate emitter, or afrequency band of an emission from the candidate emitter.
 19. The methodof claim 16, further comprising: storing information corresponding tothe candidate emitter and the candidate location in a non-transitorystorage medium.
 20. The method of claim 16, further comprising:transmitting information corresponding to the candidate emitter and thecandidate location to a communications bus or to an informationprocessing node.
 21. The method of claim 1, wherein the first sensingdevice and the second sensing device include at least one of a Low EarthOrbit (LEO) satellite, a Medium Earth Orbit (MEO) satellite, aGeosynchronous Orbit (GEO) satellite, a Highly Elliptical Orbit (HEO)satellite, a nano satellite, an unmanned aerial vehicle (UAV), aterrestrial vehicle, a spacecraft, or a mobile platform.
 22. The methodof claim 1, wherein the first sensing device includes the second sensingdevice and is configured to receive a plurality of radio signals, andwherein obtaining the second information corresponding to the secondradio signal comprises obtaining the second information corresponding tothe second radio signal received at the first sensing device.
 23. Themethod of claim 1, wherein the first sensing device or the secondsensing device includes the information combining node, and whereintransmitting at least one of the first metadata or the second metadatato the information combining node comprises transmitting at least one ofthe first metadata or the second metadata to one of the first sensingdevice and the second sensing device that includes the informationcombining node.
 24. The method of claim 1, wherein the first cost metriccomprises a mean squared value corresponding to the difference betweenthe first reconstructed signal and the first radio signal, and whereinthe second cost metric comprises a mean squared value corresponding tothe difference between the second reconstructed signal and the secondradio signal.
 25. The method of claim 1, wherein the informationcombining node includes a plurality of information combining nodes thatcomprise a data center, a ship control center, or a satellite controlcenter.
 26. A non-transitory computer-readable medium storinginstructions that, when executed by one or more processors, areconfigured to cause the one or more processors to perform operationscomprising: obtaining, from a first sensing device, first informationcorresponding to a first radio signal received at the first sensingdevice from a candidate location; determining a first reconstructedsignal corresponding to the first radio signal based on the firstinformation; determining at least one of a first time-estimate or afirst frequency-estimate based on a correlation between the first radiosignal and the first reconstructed signal; determining first metadatacorresponding to the first radio signal based on at least one of thefirst information, the first time-estimate, or the firstfrequency-estimate; obtaining, from a second sensing device, secondinformation corresponding to a second radio signal received at thesecond sensing device from the candidate location; determining a secondreconstructed signal corresponding to the second radio signal based onthe second information; determining at least one of a secondtime-estimate or a second frequency-estimate based on correlationbetween the second radio signal and the second reconstructed signal;determining second metadata corresponding to the second radio signalbased on at least one of the second information, the secondtime-estimate, or the second frequency-estimate; transmitting at leastone of the first metadata or the second metadata to an informationcombining node; obtaining, from the information combining node, at leastone of the first metadata or the second metadata; determining arelationship between the first metadata and the second metadata; anddetermining the candidate location based on the first metadata, thesecond metadata, and the relationship between the first metadata and thesecond metadata, wherein transmitting at least one of the first metadataor the second metadata to the information combining node comprisesrestricting transmission of the first radio signal and the second radiosignal to the information combining node based on a bandwidth of thefirst sensing device, the second sensing device, or the informationcombining node, wherein determining the first reconstructed signalcomprises minimizing a first cost metric corresponding to a differencebetween the first reconstructed signal and the first radio signal, andwherein determining the second reconstructed signal comprises minimizinga second cost metric corresponding to a difference between the secondreconstructed signal and the second radio signal.
 27. The non-transitorycomputer-readable medium of claim 26, wherein a bandwidth fortransmitting the first metadata from the first sensing device is lessthan a bandwidth for transmitting the first radio signal from the firstsensing device, wherein a bandwidth for transmitting the second metadatafrom the second sensing device is less than a bandwidth for transmittingthe second radio signal from the second sensing device, wherein a memoryspace for storing the first metadata from the first sensing device isless than a memory space for storing the first radio signal from thefirst sensing device, and wherein a memory space for storing the secondmetadata from the second sensing device is less than a memory space forstoring the second radio signal from the second sensing device.
 28. Asystem comprising: a first sensing device and a second sensing device;one or more processors; and a storage medium storing instructions that,when executed by the one or more processors, are configured to cause theone or more processors to perform operations comprising: obtaining, fromthe first sensing device, first information corresponding to a firstradio signal received at the first sensing device from a candidatelocation; determining a first reconstructed signal corresponding to thefirst radio signal based on the first information; determining at leastone of a first time-estimate or a first frequency-estimate based on acorrelation between the first radio signal and the first reconstructedsignal; determining first metadata corresponding to the first radiosignal based on at least one of the first information, the firsttime-estimate, or the first frequency-estimate; obtaining, from thesecond sensing device, second information corresponding to a secondradio signal received at the second sensing device from the candidatelocation; determining a second reconstructed signal corresponding to thesecond radio signal based on the second information; determining atleast one of a second time-estimate or a second frequency-estimate basedon correlation between the second radio signal and the secondreconstructed signal; determining second metadata corresponding to thesecond radio signal based on at least one of the second information, thesecond time-estimate, or the second frequency-estimate; transmitting atleast one of the first metadata or the second metadata to an informationcombining node; obtaining, from the information combining node, at leastone of the first metadata or the second metadata; determining arelationship between the first metadata and the second metadata; anddetermining the candidate location based on the first metadata, thesecond metadata, and the relationship between the first metadata and thesecond metadata, wherein transmitting at least one of the first metadataor the second metadata to the information combining node comprisesrestricting transmission of the first radio signal and the second radiosignal to the information combining node based on a bandwidth of thefirst sensing device, the second sensing device, or the informationcombining node, wherein determining the first reconstructed signalcomprises minimizing a first cost metric corresponding to a differencebetween the first reconstructed signal and the first radio signal, andwherein determining the second reconstructed signal comprises minimizinga second cost metric corresponding to a difference between the secondreconstructed signal and the second radio signal.
 29. The system ofclaim 28, wherein a bandwidth for transmitting the first metadata fromthe first sensing device is less than a bandwidth for transmitting thefirst radio signal from the first sensing device, wherein a bandwidthfor transmitting the second metadata from the second sensing device isless than a bandwidth for transmitting the second radio signal from thesecond sensing device, wherein a memory space for storing the firstmetadata from the first sensing device is less than a memory space forstoring the first radio signal from the first sensing device, andwherein a memory space for storing the second metadata from the secondsensing device is less than a memory space for storing the second radiosignal from the second sensing device.